As many high school or college students could tell you, books about statistics can be rather dry. Exploring Everyday Things with R and Ruby turns this preconception on its head, with author Sau Sheong Chang providing a sequence of fun exercises that introduces the reader to the basics of programming and data analysis.

The book’s format is simple enough: Each chapter presents a different real-world scenario or question that could benefit from some sort of quantitative analysis. The first few chapters offer quick tutorials on the two primary tools used in the book: Ruby for data collection/formatting and R for the statistical analysis and graphs. While the pace of these tutorials can seem a bit hurried in places or perhaps be a little overwhelming for those without any programming experience, Chang really does do a good job of choosing what parts of R and Ruby are relevant to the task at hand and providing succinct documentation about they work.

Of course, the breadth of examples are what make Chang’s book stand out. Each scenario uses a different discipline as its home base: sociology, data mining, cardiology, economics, and ethology all brought to bear in one form or another. Chang also uses the scenarios to introduce the reader to a bunch of useful Ruby libraries and toolsets, even showing how to play around with .wav files in a hex editor! Each scenario is simplified enough to make the underlying code accessible, but also contains enough complexity to show the reader that these quantitative techniques really can lead to useful insights.

While many technical books focus on the intricacies of the particular programming language at hand, Exploring Everyday Things reminds us that these tools are ultimately used for some real-world purpose. By combining a concise but solid foundation in statistical analysis with fun applications across a wide variety of professional arenas, this book should have no problem getting the reader excited about exploring the world around them. In fact, given how well-rounded the book is, I wouldn’t be surprised if it started showing up as required reading for liberal arts or interdisciplinary curricula that have a computer science component. Bringing open source tools to bear on everyday problems is proving to be an immensely useful skill, and one that college students should be exposed to whenever possible. Here’s hoping that O'Reilly has more books like this in the pipeline.